Data integration problem of structural and semantic heterogeneity
Preeti Patil, S Govinda Rao, Sharad B. Patil · 2011
Data Warehouse plays an important part in the process of knowledge engineering and decision-making for Enterprise, as a key component of the data warehouse architecture, the tool that support data extraction, transformation, loading (ETL) is a critical success factor for any data warehouse projects [2, 5, 7]. Traditional methods of ETL development are pieces of software responsible for the extraction of data from several sources, their cleansing, customization, and insertion into a data warehouse [1, 6]. To solve heterogeneity problems of different data sources in the processes, this paper reviewed framework models [7] for optimization of the ETL processes by using semantic web technologies and discusses how ontologies are used to support the data integration. A metadata management System with good design can highly improve the ETL efficiency [1, 2, 6, and 10]. There are different strategies that can be used and they each have different costs and benefits.